IIBA.org CBDA Competencies

CBDA Competencies

Certification in Business Data Analytics IIBA®-CBDA

Competencies and Proficiency Levels per Knowledge Area

Definitions of skill and knowledge levels used.
Practical Knowledge or General Awareness:

Limited practical experience. Expertise is developed in a safe, structured environment (small, less complex efforts) where guidance is both sought and provided.

Basic Knowledge: Has a fundamental awareness of basic skills and knowledge involved in the work.

Understands: Recognizes the key elements of the work and why they are important. However, not expected to have the experience nor skill to execute.

Follows Rules: Adheres to prescribed ways to complete the work but needs rules and guidelines to successfully execute.

The competency elements are grouped into six Knowledge Areas:

Five of the knowledge areas are practitioner-based domains as discussed in IIBA’s Introduction to Business Data Analytics: A Practitioners View; and one is an organizational-based domain from IIBA’s Introduction to Business Data Analytics: An Organizational View.

1: Identify Research Questions

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1.1.1 General Awareness: Understands the problems or opportunities the business wants to address

1.1.2 Practical Knowledge: Follows Rules to define the business need

1.1.3 Practical Knowledge: Follows Rules to analyze the current state to understand the existing environment

1.1.4 General Awareness: Understands the future state including the outcomes being sought from the analytics research

1.1.5 General Awareness: Understands determining gaps between current and future state

1.1.6 General Awareness: Understands the KPIs and/or metrics to gauge success

1.1.7 General Awareness: Understands determining the scope of the analytics effort

1.1.8 General Awareness: Understands determining analytics assumptions, constraints, dependencies

1.1.9 General Awareness: Basic Knowledge of the organization’s current state of analytics, including current culture, practices, skills, systems, and data

1.2.1 General Awareness: Basic Knowledge of defining how analytics work will be performed

1.2.2 General Awareness: Understands formulating the research questions that analytics will be used to answer

1.2.3 General Awareness: Basic Knowledge of determining the activities, deliverables, models

1.2.4 General Awareness: Basic Knowledge of picking tools & techniques based on the category of analytics

1.2.5 General Awareness: Basic Knowledge of the sequence of work activities

1.2.6 General Awareness: Understands obtaining approval on approach including research question

2: Source Data

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2.1.1 General Awareness: Basic Knowledge of what data is needed to answer the research question

2.2.2 General Awareness: Understands to contribute expertise about data required/available

2.2.1 General Awareness: Understands determining what data is already collected and what new data is needed

2.2.2 General Awareness: Basic Knowledge of the data sources that make up the data set (data lakes, marts, vaults, warehouse)

2.3.1 General Awareness: Basic Knowledge of identifying data frequency and flow

2.3.2 General Awareness: Understands assessing the quality of data

2.4.1 General Awareness: Basic Knowledge of determining sample size

2.4.2 General Awareness: Basic Knowledge of supporting data scientists with data sampling

2.4.3 General Awareness: Understands establishing/identifying relationships in data

2.4.4 General Awareness: Basic Knowledge of dependencies between data e.g., clustering/sensitivity analysis

2.4.5 General Awareness: Basic Knowledge of data linkages between data sources

2.4.6 General Awareness: Basic Knowledge of acquiring data

2.4.7 General Awareness: Basic Knowledge of pre-process/cleaning data

2.4.8 General Awareness: Understands assessing data integrity/quality

2.4.9 General Awareness: Understands detecting outliers/noise/features from a data set

2.4.10 General Awareness: Basic Knowledge of adjusting the data acquisition approach as needed

3: Analyze Data

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3.1 General Awareness: Understands producing scope, data, and decision models

3.2 General Awareness: Basic Knowledge of creating architectural diagrams

3.3 General Awareness: Basic Knowledge of developing mathematical models

3.4 General Awareness: Basic Knowledge of suggesting and implementing predictive models such as regression, logistics regression, decision trees/random forest, neural nets, etc.

3.5 General Awareness: Basic Knowledge of preparing data

3.6 General Awareness: Basic Knowledge of performing data analysis

3.7 General Awareness: Understands whether the analytics results are helping to answer the business question

3.8 General Awareness: Basic Knowledge of adjusting to the analytics approach as needed, based on results obtained

3.9 General Awareness: Basic Knowledge of interpreting regression output and adjust models as needed

4: Interpret and Report Results

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4.1 General Awareness: Understands interpreting results

4.2 General Awareness: Understands deriving insights from the results of analysis

4.3 General Awareness: Understands refining problem/opportunity statements based on findings

4.4 General Awareness: Understands putting forth recommendations from insights derived

4.5 Practical Knowledge: Follows Rules to develop the business narrative to explain results to the business

4.6 Practical Knowledge: Follows Rules in developing visualizations to help with communications

4.7 Practical Knowledge: Follows Rules in preparing the analytics package to communicate

4.8 Practical Knowledge: Follows Rules in determining how best to package and communicate

4.9 Practical Knowledge: Follows Rules in determining stakeholder communication needs

5: Use Results to Influence Business Decision Making

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5.1 General Awareness: Understands determining if analytics results answer the research question

5.2 General Awareness: Understands assessing how well the analytics results are meeting the business need

5.3 Practical Knowledge: Follows Rules in assessing proposed solution and recommending action

5.4 General Awareness: Understands developing an implementation plan

5.5 Practical Knowledge: Follows Rules in assessing organizational readiness and managing change

6: Guide Company-level Strategy for Business Analytics

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6.1.1 General Awareness: Understands the process of transforming analysis results back into policies and procedures within an organization

6.2.1 General Awareness: Understands assessing the proposed analytics solution

6.2.2 General Awareness: Basic Knowledge of measuring the behavior or outcome of data-driven decisions that are made

6.2.3 General Awareness: Basic Knowledge of assessing the analytics and system approach

6.2.4 General Awareness: Understands assessing organizational readiness including identified gaps, resources, data, automation readiness and asking the right questions:

Is the organization ready for automation of analytics?
Does the organization have the right data?

6.3.1 General Awareness: Basic Knowledge to ensure that data is represented consistently

6.3.2 Practical Knowledge: Follows Rules in contributing to the maintenance of a glossary

6.3.3 General Awareness: Basic Knowledge of data security

6.3.4 General Awareness: Basic Knowledge of performing data validation for metrics / KPIs

6.4.1 General Awareness: Understands building internal reporting/analytics dashboards

6.4.2 General Awareness: Understands scanning and cataloging the data assets in a company

6.5.1 General Awareness: Basic Knowledge of the differences between master data and operational and transactional data

6.5.2 General Awareness: Basic Knowledge of identifying and applying data privacy rules

6.6.1 General Awareness: Basic Knowledge of ensuring that a standard set of tools/techniques are identified, and best practices adhered to

6.6.2 General Awareness: Basic Knowledge on providing information about best practices and adherence to standards

6.6.3 General Awareness: Basic Knowledge of ensuring that sampling methods are shared across teams (where meaningful) and understood by all

6.6.4 General Awareness: Basic Knowledge of maintaining analytics requirements for re-use